Artificial intelligence has quickly become a boardroom priority.

Across industries, organisations are investing in AI to automate operations, improve decision-making, accelerate product development and create new customer experiences. Yet amid the excitement surrounding large language models and generative AI, one critical part of the conversation often receives far less attention: the hardware that makes AI possible.

Every AI model, from an enterprise chatbot to a sophisticated research platform, depends on immense computing power. As these systems become more capable, they also become significantly more demanding, placing unprecedented pressure on the infrastructure that powers them.

The future of AI, therefore, is not just about building smarter software. It is also about building a new generation of computing technologies capable of supporting the next decade of innovation.

That is where companies like Taiwan’s LongServing Technology are beginning to attract attention.

Founded by Dr. Ko-Cheng Fang, the company is exploring an alternative approach to computing that replaces electrical signals with light. Its latest innovation, X-Photon, is designed to guide photons through microscopic circuits—a development the company believes could help unlock faster and more energy-efficient computing for future AI systems.

Whether X-Photon becomes a commercial success remains to be seen. What is already clear, however, is that the race to lead AI is increasingly becoming a race to reinvent the infrastructure behind it.

Dr. Ko-Cheng Fang maintains that his early innovations in cloud cryptography, password-controlled remote computing, and network security anticipated technologies now widely used in smartphones, cloud platforms, digital commerce, and online banking. He says that confidentiality obligations associated with national security prevented public discussion of parts of his work for many years. Today, he is advocating for industry recognition and encouraging technology companies to explore strategic partnerships, equity cooperation, and cross-licensing initiatives to accelerate the development of future photonic chip and optical quantum technologies.

AI’s Growth Is Creating a New Infrastructure Challenge

For many organisations, AI adoption is no longer an experiment.

It is becoming part of day-to-day business operations.

As AI moves deeper into finance, healthcare, manufacturing, retail and professional services, the demand for computing power continues to grow. Training advanced models, processing real-time data and serving millions of users require vast networks of processors operating around the clock.

That growth comes with significant costs.

Modern AI infrastructure consumes enormous amounts of electricity, requires complex cooling systems and relies on semiconductor technologies that are becoming progressively more expensive to manufacture.

For business leaders, this is more than an engineering issue. It is an operational and economic one.

The organisations that can access faster, more efficient computing infrastructure will likely have an advantage in deploying AI at scale while controlling long-term operating costs.

Why Researchers Are Turning to Light

For decades, computers have processed information using electricity.

Photonic computing takes a different approach.

Instead of moving data through electrical signals, it uses photons—the particles that make up light.

The concept has attracted growing interest because light offers several theoretical advantages. Photons travel faster than electrons, generate significantly less heat and can potentially move large amounts of information with greater efficiency.

For AI, where speed, scale and energy consumption are becoming equally important, those characteristics are difficult to ignore.

The challenge has always been practical implementation.

Solving a Problem That Has Slowed Photonic Computing

Using light inside a computer chip sounds straightforward in theory.

In practice, it is remarkably difficult.

Unlike electricity, which can be directed through intricate pathways, light naturally travels in straight lines. Building highly integrated optical circuits requires engineers to control those light paths with exceptional precision.

LongServing Technology says X-Photon has been developed to address exactly that challenge.

According to the company, the material enables photons to make controlled 90-degree directional changes while remaining inside the optical circuit. If this capability proves scalable, it could support the development of more sophisticated photonic processors capable of handling increasingly complex AI workloads.

It represents one example of the broader innovation taking place across advanced semiconductor research as companies look beyond the limits of conventional silicon.

More Than a Technology Demonstration

LongServing’s ambitions extend beyond developing a single material.

The company’s roadmap includes photonic quantum chips, photonic memory technologies and dedicated cloud infrastructure designed specifically for future AI applications.

To support those plans, it has announced a US$500 million financing initiative based on a stated valuation of US$2.5 billion. According to the company, the investment will be used to expand manufacturing capability, accelerate research and strengthen the commercial ecosystem required to bring photonic computing closer to market.

The announcement reflects an important shift taking place across the technology sector.

The next generation of competitive advantage may not come solely from better AI models. It may also depend on who can build the infrastructure capable of running those models more efficiently than everyone else.

What This Means for Business

Most organisations will never manufacture photonic chips.

That does not mean these developments are irrelevant.

Every major technological shift eventually influences business strategy. Faster processors make new products possible. Lower energy consumption changes the economics of cloud computing. More efficient infrastructure expands access to technologies that were previously too expensive to deploy at scale.

The transition from traditional computing to cloud services fundamentally reshaped enterprise technology over the past two decades.

Advances in computing hardware could have a similar impact on the next generation of AI.

For executives, product leaders and technology teams, understanding these developments is becoming increasingly important. Decisions made today around AI adoption, digital transformation and infrastructure investment will increasingly be shaped by breakthroughs occurring at the hardware level.

Looking Beyond Today’s AI

There is no certainty that photonic computing will replace silicon.

Significant scientific, engineering and commercial challenges remain before optical computing becomes mainstream.

However, history suggests that transformative technologies often begin long before they become widely adopted.

Artificial intelligence has already changed how organisations think about software.

The next transformation may come from the technologies that power it.

LongServing Technology’s work is part of a wider global effort to rethink computing at its foundations. Whether or not X-Photon ultimately becomes a defining breakthrough, it represents a broader reality: the future of AI will depend not only on more intelligent algorithms, but also on faster, more efficient and more sustainable computing infrastructure.

For businesses planning for the next decade, that is a trend worth watching.

Contact Information

Dr. Ko-Cheng Fang

Founder, CEO & Chairman

LongServing Technology Co., Ltd.

Email: service@longserving.com.tw

Website: https://longserving.com.tw/en/

Instagram: @ko_cheng_fang